This workshop will present recent methods of mapping sequence reads generated by an RNA-seq experiment to a reference genome (human genome),assigning reads to genome features (exon, intron, etc), and using the expression levels of those features to identify differentially expressed genes between different conditions (cancer vs normal, treated vs untreated, etc). We will examine some of the methods, their principles and biases in every step. We will look at techniques to quantify our results, and some of the pitfalls to be aware of. At the end of this workshop, participants will have the ability to perform analysis of a realistic/own dataset, from data retrieval through differential gene expression, and have an appreciation of the available data sources and tools, be deeply aware of biases, and be able to use these insights to critically interpret the results.

Objectives

To give participants a combination of lecture and hands-on bioinformatics analysis